Add language tags
#2
by
lbourdois
- opened
README.md
CHANGED
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@@ -1,5 +1,109 @@
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---
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language:
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license: apache-2.0
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datasets:
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- wikipedia
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@@ -22,8 +126,7 @@ datasets:
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## Model Description
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This model is a distilled version of the [BERT base multilingual model](bert-base-multilingual-cased). The code for the distillation process can be found
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[here](https://github.com/huggingface/transformers/tree/master/examples/distillation). This model is cased: it does make a difference between english and English.
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The model is trained on the concatenation of Wikipedia in 104 different languages listed [here](https://github.com/google-research/bert/blob/master/multilingual.md#list-of-languages).
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The model has 6 layers, 768 dimension and 12 heads, totalizing 134M parameters (compared to 177M parameters for mBERT-base).
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| 1 |
---
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+
language:
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- multilingual
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- af
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- sq
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- ar
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- an
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- hy
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- ast
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- az
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- ba
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- eu
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- bar
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- be
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- bn
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- inc
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- bs
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- br
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- bg
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- my
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- ca
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- ceb
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- ce
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- zh
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- cv
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- hr
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- cs
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- da
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- nl
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- en
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- et
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- fi
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- fr
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- gl
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- ka
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- de
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- el
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- gu
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- ht
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- he
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- hi
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- hu
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- is
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- io
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- id
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- ga
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- it
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- ja
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- jv
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- kn
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- kk
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- ky
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- ko
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- la
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- lv
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- lt
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- roa
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- nds
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- lm
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- mk
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- mg
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- ms
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- ml
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- mr
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- mn
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- min
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- ne
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- new
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- nb
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- nn
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- oc
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- fa
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- pms
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- pl
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- pt
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- pa
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- ro
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- ru
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- sco
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- sr
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- hr
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- scn
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- sk
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- sl
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- aze
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- es
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- su
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- sw
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- sv
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- tl
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- tg
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- th
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- ta
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- tt
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- te
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- tr
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- uk
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- ud
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- uz
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- vi
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- vo
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- war
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- cy
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- fry
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- pnb
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- yo
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license: apache-2.0
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datasets:
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- wikipedia
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## Model Description
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| 128 |
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+
This model is a distilled version of the [BERT base multilingual model](https://huggingface.co/bert-base-multilingual-cased/). The code for the distillation process can be found [here](https://github.com/huggingface/transformers/tree/main/examples/research_projects/distillation). This model is cased: it does make a difference between english and English.
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The model is trained on the concatenation of Wikipedia in 104 different languages listed [here](https://github.com/google-research/bert/blob/master/multilingual.md#list-of-languages).
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The model has 6 layers, 768 dimension and 12 heads, totalizing 134M parameters (compared to 177M parameters for mBERT-base).
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